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Focusing on the problem of how to partition the cache space given to a multithreaded application across its threads, we show that different threads of a multithreaded application can have different cache space requirements, propose a fully automated, dynamic, intra-application cache partitioning scheme targeting emerging multicores with multilayer cache hierarchies, present a comprehensive experimental analysis of the proposed scheme, and show average improvements of 17.1% and 18.6% in SPECOMP and PARSEC suites. 3

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The objectives and the implementation are different on cache partition. The intra-application cache partition tries to minimize the latency of the slowest thread.  Runtime system or dynamic compiler The inter-application cache partition tries to optimize workload throughput.  OS problem 6

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Dynamic Partition System Helper Thread whose main responsibility is to partition the cache space allocated to the application to maximize its performance. System Interfacing Performance Monitoring Performance Modeling

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Use Average Memory Access Time as measure of the cache performance of a thread. AMAT  The ratio of total cycles spent on memory instructions and total number of instructions  Depends on the cache partition size  Take into account with different level of cache 9

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Need to predict the impact of increasing and decreasing the cache space to a thread. Expressed a thread with 3D plot  X and Y respectively for cache space allocation from L2 and L3 Thread i, point d(s L2, s L3 ) value to build dynamic model for thread i. Purpose – predict the performance of a thread 10

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i th L2 cache, q L2,i denotes the total cache way allocated to this application. q L2,i are shared by m L2,i thread(from 0 to m L2,i ) The number of ways allocated to the k th thread is denoted as s L2,i (k) 11

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18 Shows that balancing the data access latency of different threads. As the execution went on, they all end up at about 8 AMAT(cycle).

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Intra-application cache partitioning for multithread Dynamic model, able to partition cache in multiple layer. Average improvement of 17.1% in SECOMP and 18.6% in PARSEC. My Comment  Remind me the importance of software and hardware cooperation.  Thread is a main issue in CMP. 19